The availability of spatial information in a situation model

Four experiments were conducted to determine the availability of spatial information from a situation model. In Experiment 1, participants were told to either focus on spatial information while reading the texts or to read for comprehension. At the end of each text, participants were presented with a probe word to name. The probe word was either spatially associated or dissociated with the final spatial location of the main character. Participants named the spatial probe more quickly only when told to focus on spatial information. Experiment 2 used reading time as a dependent measure to determine ease of integration of spatially associated or dissociated information. Again, participants were told either to focus on spatial information or to read for comprehension. Participants noticed a violation of coherence between the critical sentence and previously presented spatial information only when told to focus on spatial information. Experiments 3 and 4 replicated Experiments 1 and 2 respectively, with re-written passages designed to implicitly encourage the readers to focus on spatial information. In Experiment 3 participants named spatial probe more quickly only when told to focus on spatial information. However, in Experiment 4, participants noticed a violation of coherence regardless of explicit experimental instructions. Results are discussed within the Construction-Integration model (Kintsch, 1988)

Traffic Situation Model

Tato práce se zabývá identifikací parametrů potřebných pro fyzickou realizaci modelu dopravního kamerového systému. Tyto informace jsou pak využity k návrhu a konstrukci modelu, který bude schopný simulovat důležité dopravní situace. Pozornost je pak věnována schopnosti modelu přijímat instrukce s pomocí k tomuto účelu implementovaného komunikačního rozhraní. Práce se poté zabývá vytvořením aplikačního rozhraní, které umožní ovládání skupiny kamer a získání obrazu z nich. Vlastnosti aplikace jsou takové, aby umožnily budoucí využití kamer pro měření úsekové rychlosti a detekci průjezdu na červenou.In this thesis, parameters required for physical construction of model of traffic camera system are identified. The information is used to design and construct a model, which supports simulation of important traffic situations. With focus, on the ability of model to allow for digital modification of simulation parameters over, for this purpose created, communication interface. The next part of thesis then focuses on creation of application which supports the control and image retrieval from group of cameras. The application is designed to support settings necessary for use as average speed enforcement cameras and as red-light cameras.

Bankruptcy Situation Model in Small Business: The Case of Restaurant Firms

The purpose of this paper is to describe and discuss the current bankruptcy prediction models. This is done in the context of pros and cons of proposed models to determine the appropriate factors of failure phenomenon in cases involving restaurants that have filed for bankruptcy under Chapter 11. A sample of 11 restaurant companies that filed for bankruptcy between 1993 and 2003 were identified from the Form 8-K reported to the Securities and Exchange Commission (SEC). By applying financial ratios retrieved from the annual reports which contain, income statements, balance sheets, statements of cash flows, and statements of stockholders’ equity (or deficit) to the Atlman’s mode, Springate model, and Fulmer’s model. The study found that Atlman’s model for the non-manufacturing industry provided the most accurate bankruptcy predictions

Moving Beyond Words: Supporting Text Processing Using a Situation Model approach

Krabbendam, A.C. [Promotor]Schoot, M. van der [Copromotor]Koning, B.B. de [Copromotor

Learning Situation Models in a Smart Home

International audienceThis article addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart envi- ronment is represented by a situation model describing environment, users and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and the evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach

SMART: A Situation Model for Algebra Story Problems via Attributed Grammar

Solving algebra story problems remains a challenging task in artificial intelligence, which requires a detailed understanding of real-world situations and a strong mathematical reasoning capability. Previous neural solvers of math word problems directly translate problem texts into equations, lacking an explicit interpretation of the situations, and often fail to handle more sophisticated situations. To address such limits of neural solvers, we introduce the concept of a \emph{situation model}, which originates from psychology studies to represent the mental states of humans in problem-solving, and propose \emph{SMART}, which adopts attributed grammar as the representation of situation models for algebra story problems. Specifically, we first train an information extraction module to extract nodes, attributes, and relations from problem texts and then generate a parse graph based on a pre-defined attributed grammar. An iterative learning strategy is also proposed to improve the performance of SMART further. To rigorously study this task, we carefully curate a new dataset named \emph{ASP6.6k}. Experimental results on ASP6.6k show that the proposed model outperforms all previous neural solvers by a large margin while preserving much better interpretability. To test these models' generalization capability, we also design an out-of-distribution (OOD) evaluation, in which problems are more complex than those in the training set. Our model exceeds state-of-the-art models by 17\% in the OOD evaluation, demonstrating its superior generalization ability

Validating a Theory-based Model of L2 Reading Comprehension: Relative contributions of content-specific schematic knowledge and L2 vocabulary knowledge to comprehending a science text

The study explores the question of what explains second language (L2) reading comprehension by proposing a comprehensive theory building on the Construction Integration (CI) model of reading comprehension (Kintsch, 1998) and conducting an experimental study within this theoretical framework. The proposed theory maintains that the construction of a textbase is a function of L2 proficiency and the construction of a situation model is a function of first language (L1) reading competence. The effect of two different types of intervention tapping into each representation system (textbase and situation model) is experimentally tested; vocabulary knowledge, conducive to building textbase, and content-specific schematic knowledge, facilitative to building situation model. Two different measures of reading comprehension for both L1 and L2 reading comprehension are used to analyze how different cognitive processes are involved in L2 reading comprehension. Thirty two 9th grade Korean students were given a vocabulary acquisition activity and a content-specific schematic knowledge acquisition activity between a pretest and a posttest on science texts. The findings suggest that the ability to form macropropositions, as measured by a recall task, is a route through which L1 reading competence emerges. Thus, it is an influential factor for L2 reading comprehension. Different patterns in the role of L1 reading competence and L2 proficiency in different treatment conditions provide evidence for a reader constructing a textbase as a function of L2 proficiency and a reader constructing a situation model as a function of L1 reading competence. Three latent variables of textbase, situation model, and L2 reading comprehension were entered in LISREL to conduct structural equation modeling; the indicators of the textbase include the scores of vocabulary knowledge and the scores of listening comprehension (LC) and reading comprehension (RC) in an L2 proficiency measure; the indicators of the situation model include the scores of L1 reading competence and the scores of schematic knowledge; and the indicators of L2 reading comprehension include the scores of the pretests and the posttests. The fit indices of various Structural Equation Modeling (SEM) models of a given text demonstrate the viability of the comprehensive theory of L2 reading comprehension